Evidence map›Paper›PMID 37302817›Full record

ArticleBritish journal of pharmacology2023

Virtual drug screen reveals context-dependent inhibition of cardiomyocyte hypertrophy.

Taylor G Eggertsen, Jeffrey J Saucerman

Open access · bronzeAbstract read
In one paragraph

Article in British journal of pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Striking the balance: Complexity, simplicity, and credibility in mathematical biology.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Advances in Drug Discovery for Cardiomyocyte Proliferation.Current treatment options in cardiovascular medicine · 2025
    Review
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Taylor G EggertsenDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.ORCID 0000-0002-2149-9686
Jeffrey J SaucermanDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.
University of Virginia · US

Funding

BASIC CARDIOVASCULAR RESEARCH TRAINING GRANTT32HL007284 · NHLBI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Brant E Isakson, Gary K Owens · 1985 to 2026
$19.6M
Systems Pharmacology Model of Cardiac HypertrophyR01HL162925 · NHLBI · UNIVERSITY OF VIRGINIA · PI SAUCERMAN, JEFFREY J., WOLF, MATTHEW J · 2022 to 2025
$3.1M
Computational and Experimental Modeling of Cardiomyocyte ProliferationR01HL160665 · NHLBI · UNIVERSITY OF VIRGINIA · PI SAUCERMAN, JEFFREY J., VAN BERLO, JOHANNES (JOP) · 2022 to 2025
$2.8M
Systems Pharmacology Model for Spatial Control of Cardiac FibrosisR01HL137755 · NHLBI · UNIVERSITY OF VIRGINIA · PI HOLMES, JEFFREY W, SAUCERMAN, JEFFREY J. · 2017 to 2020
$1.9M
Virtual drug screen reveals context-dependent inhibition of cardiomyocyte hypertrophyF31HL168849 · NHLBI · UNIVERSITY OF VIRGINIA · PI EGGERTSEN, TAYLOR · 2023 to 2024
$44k
NHLBI NIH HHS F31 HL168849NHLBI NIH HHS R01 HL137755NHLBI NIH HHS R01 HL160665NHLBI NIH HHS R01 HL162925NHLBI NIH HHS T32 HL007284
6 · The paper itself

Abstract

background and purposePathological cardiomyocyte hypertrophy is a response to cardiac stress that typically leads to heart failure. Despite being a primary contributor to pathological cardiac remodelling, the therapeutic space that targets hypertrophy is limited. Here, we apply a network model to virtually screen for FDA-approved drugs that induce or suppress cardiomyocyte hypertrophy. EXPERIMENTAL APPROACH: A logic-based differential equation model of cardiomyocyte signalling was used to predict drugs that modulate hypertrophy. These predictions were validated against curated experiments from the prior literature. The actions of midostaurin were validated in new experiments using TGFβ- and noradrenaline (NE)-induced hypertrophy in neonatal rat cardiomyocytes. KEY

resultsModel predictions were validated in 60 out of 70 independent experiments from the literature and identify 38 inhibitors of hypertrophy. We additionally predict that the efficacy of drugs that inhibit cardiomyocyte hypertrophy is often context dependent. We predicted that midostaurin inhibits cardiomyocyte hypertrophy induced by TGFβ, but not noradrenaline, exhibiting context dependence. We further validated this prediction by cellular experiments. Network analysis predicted critical roles for the PI3K and RAS pathways in the activity of celecoxib and midostaurin, respectively. We further investigated the polypharmacology and combinatorial pharmacology of drugs. Brigatinib and irbesartan in combination were predicted to synergistically inhibit cardiomyocyte hypertrophy. CONCLUSION AND IMPLICATIONS: This study provides a well-validated platform for investigating the efficacy of drugs on cardiomyocyte hypertrophy and identifies midostaurin for consideration as an antihypertrophic drug.

Indexed as

Heart FailureMyocytes, CardiacAnimalsCardiomegalyCells, CulturedRatsSignal TransductionTransforming Growth Factor betaTransforming Growth Factor betacardiomyocytehypertrophymidostaurinnetwork modelTGFβ

Identifiers

PMID37302817
PMCPMC10592153
OpenAlexW4380224927

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.